Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technologies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. The first XPS and XRF intensity signals include information for the first layer and for the substrate. The method also involves determining a thickness of the first layer based on the first XPS and XRF intensity signals. The method also involves combining the information for the first layer and for the substrate to estimate an effective substrate. The method also involves measuring second XPS and XRF intensity signals for a sample having a second layer above the first layer above the substrate. The second XPS and XRF intensity signals include information for the second layer, for the first layer and for the substrate.

Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technologies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. The first XPS and XRF intensity signals include information for the first layer and for the substrate. The method also involves determining a thickness of the first layer based on the first XPS and XRF intensity signals. The method also involves combining the information for the first layer and for the substrate to estimate an effective substrate. The method also involves measuring second XPS and XRF intensity signals for a sample having a second layer above the first layer above the substrate. The second XPS and XRF intensity signals include information for the second layer, for the first layer and for the substrate.

Abstract: Methods and systems for feed-forward of multi-layer and multi-process information using XPS and XRF technologies are disclosed. In an example, a method of thin film characterization includes measuring first XPS and XRF intensity signals for a sample having a first layer above a substrate. The first XPS and XRF intensity signals include information for the first layer and for the substrate. The method also involves determining a thickness of the first layer based on the first XPS and XRF intensity signals. The method also involves combining the information for the first layer and for the substrate to estimate an effective substrate. The method also involves measuring second XPS and XRF intensity signals for a sample having a second layer above the first layer above the substrate. The second XPS and XRF intensity signals include information for the second layer, for the first layer and for the substrate.

Abstract: According to one embodiment of the invention, a method for analyzing data from an instrument is disclosed. The raw data generated by the instrument, along with configuration data generated by a user, is packaged into a calling model. The raw data may include, for example, counts having a certain kinetic energy when analyzing photoelectron spectroscopy data. The configuration data may include several parameters selected by the user based on the composition and configuration of the structure being measured. The calling model may serve as an interface between the instrument and an engine for generating an algorithm for returning desired results to the user. The engine then generates the algorithm as well as the results specified by the user, and the calling model returns the results to the user. This allows a specific algorithm and results for a specific measured sample or structure to be generated using known algorithms and functions.

Abstract: According to one embodiment of the invention, a method for analyzing data from an instrument is disclosed. The raw data generated by the instrument, along with configuration data generated by a user, is packaged into a calling model. The raw data may include, for example, counts having a certain kinetic energy when analyzing photoelectron spectroscopy data. The configuration data may include several parameters selected by the user based on the composition and configuration of the structure being measured. The calling model may serve as an interface between the instrument and an engine for generating an algorithm for returning desired results to the user. The engine then generates the algorithm as well as the results specified by the user, and the calling model returns the results to the user. This allows a specific algorithm and results for a specific measured sample or structure to be generated using known algorithms and functions.